During the examination of a stream of activities, a meaningful increase in the frequency of certain events may be detected. The volume of the event may not always necessarily be of importance, but only the increase in its relative frequency. An event for which the event occurs in an increased frequency may be considered as a trend.
Trend analysis may be the practice of collecting information and attempting to spot a pattern, or trend, in the information. Although trend analysis may often be used to predict future events, it may also be used to estimate uncertain events in the past. Trend analysis may be performed on various types of events. As an example, issued queries to a search engine may be analyzed to spot a trending query. As another example, keywords in new posts to a social media platform may be analyzed to identify trending issues. As yet another example, hashtags in posts, tags in posts, or similar meta data information regarding posts may be analyzed to identify trends. Such analysis may be useful to indicate to a user which issues are currently “hot”.
In some exemplary embodiments, an event may be trending even though the number of absolute occurrences is relatively low. As an example, in October 2012, Mr. Felix Baumgartner has jumped from a helium balloon in the stratosphere. The importance of this jump to the public can be ascertained from the occurrences of the search query “felix jump”, which had increased significantly for a short period around October 2012. Even at its peak, the volume of searches for “felix jump” was insignificant compared to searches for “Justin Bieber”, however, the event is still significant and may be of interest.